Stock Performance Dashboard
Skills: Python (Pandas, Beautiful Soup), Jupyter Notebook, Data Visualization
This is a dashboard that I created using Tesla and Gamestop financial data.
The objective of this dashboard was to analyze Tesla and GameStop stock performances over the past 10-15 years. I looked at the financial data for both companies to identify patterns between the historical share price of the stock and the quarterly revenue of the company.
To collect and extract data on Tesla and GameStop, I used the yfinance and BeautifulSoup Python libraries. I also used the pandas library to create DataFrames for storing the share price and revenue data of each company.
Objective
I started by using yfinance to create a ticker object with the Ticker function to extract data on Tesla’s historical share price. I took this data and stored it into a DataFrame to display Tesla’s stock performance over the years, including the high, low, open, and close prices of the stock on any given day.
Then, I used the requests library to download a webpage displaying financial information on Tesla’s revenue. Using BeautifulSoup, I parsed this html data and extracted the quarterly revenue throughout the past 10-15 years for Tesla. After extracting this data, I stored it into another DataFrame that displayed the date and revenue for the company.
Once I had set up both DataFrames, I cleaned the data and removed any null values or empty strings. Finally, I used the make_graph function to create a set of graphs for Tesla to present the data trends for the company’s stock prices and revenue.
I repeated this process for GameStop’s financial data as well.
